Lead AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead AI Engineer based in the United States.

This is a high-impact opportunity to help establish and scale enterprise AI capabilities within a fast-growing technology environment.

You will design and deliver production-ready AI applications, agents, platforms, and reusable engineering patterns.

The role combines hands-on engineering with the opportunity to shape AI standards, governance, experimentation, and development practices.

You will help evolve traditional software development into an AI Development Lifecycle focused on continuous experimentation, evaluation, deployment, and improvement.

Working across business and technical teams, you will turn emerging AI opportunities into solutions that improve efficiency, customer experiences, and measurable business outcomes.

You will also mentor engineers and influence architecture, engineering standards, and responsible AI practices across the organization.

The environment is collaborative, fast-paced, and designed for an experienced AI engineer who enjoys building while helping define what comes next.

Accountabilities:

• Design, build, test, deploy, and maintain production-grade AI-enabled applications, generative AI solutions, AI agents, tools, and enterprise workflows.
• Establish foundational AI Center of Excellence standards, reusable architectural patterns, engineering guardrails, and implementation practices.
• Contribute to an AI experimentation lab supporting rapid prototyping, evaluation, experimentation, and iterative development of emerging AI capabilities.
• Define and operationalize AI Development Lifecycle practices covering experimentation, evaluation, governance, deployment, monitoring, and continuous improvement.
• Build reusable AI platforms, services, APIs, orchestration frameworks, and service layers that can scale across enterprise use cases.
• Identify, prioritize, and deliver AI opportunities that generate measurable operational efficiencies, customer experience improvements, or revenue impact.
• Apply modern generative AI patterns including retrieval-augmented generation, prompt engineering, agent orchestration, tool/function calling, embeddings, vector search, and human-in-the-loop workflows.
• Develop AI agents and integrate enterprise applications, APIs, tools, and data sources into reliable orchestration workflows.
• Work with large and small language models, embeddings, vector databases, model APIs, and leading AI ecosystems to select appropriate technologies for each use case.
• Design secure, observable, maintainable Python-based AI services using modern architecture patterns such as microservices, APIs, and event-driven systems.
• Establish evaluation frameworks, quality benchmarks, monitoring practices, feedback loops, and observability capabilities to continuously improve AI system performance.
• Implement responsible AI, data protection, compliance, governance, and human-oversight practices throughout the AI development lifecycle.
• Partner with business and technical stakeholders to translate problems and opportunities into scalable AI solutions, taking initiatives from concept through production and expansion.
• Create technical designs, reusable frameworks, documentation, and engineering standards that improve consistency and accelerate future AI development.
• Mentor engineers in AI engineering, AI-native development, experimentation, evaluation, and modern development practices.

Requirements

• Bachelor’s degree in Computer Science or equivalent professional experience.
• 8+ years of experience in cloud software engineering and/or AI engineering, including 8+ years of programming experience with Python.
• Hands-on experience building AI-enabled applications, generative AI solutions, AI agents, or production AI workflows.
• Strong experience with AWS and/or Azure and AI-native cloud services such as AWS Bedrock, AWS AgentCore, Azure AI Foundry, or Azure OpenAI.
• Deep understanding of generative AI concepts and implementation patterns, including LLM/SLM selection, RAG, prompt engineering, evaluation, agentic workflows, tool/function calling, embeddings, vector search, human-in-the-loop systems, and AI observability.
• Experience with agent frameworks and orchestration technologies such as LangGraph or Semantic Kernel.
• Experience working with major LLM ecosystems and providers, including OpenAI, Anthropic, Llama, Mistral, or comparable technologies.
• Hands-on experience with vector databases and retrieval platforms such as Pinecone or Azure AI Search.
• Experience with AI interoperability protocols and architectures, including AG-UI, A2A, MCP, registries, reusable service layers, or comparable standards.
• Strong experience integrating APIs, enterprise systems, data sources, and business applications into AI workflows.
• Solid understanding of modern software architecture, including microservices, APIs, event-driven systems, scalable services, and cloud-native development.
• Experience with Agile/Scrum methodologies and modern software delivery practices.
• Understanding of AI governance, responsible AI, data protection, privacy, security, and compliance considerations.
• Ability to translate ambiguous business challenges into practical AI solutions with measurable outcomes.
• Strong analytical, problem-solving, communication, collaboration, and stakeholder-management skills.
• Self-directed and comfortable operating in an evolving environment where AI standards and technologies are continually changing.
• Experience contributing to an AI Center of Excellence, AI platform, or AI innovation team is preferred.
• Experience defining or implementing an AI Development Lifecycle and structured Context Engineering practices is a plus.
• Familiarity with observability and evaluation tools such as OpenTelemetry, Datadog, CloudWatch, or LangSmith is preferred.
• Experience with CI/CD, containers, infrastructure automation, regulated environments, or AI governance frameworks such as ISO/IEC 42001 or NIST AI RMF is advantageous.
• Demonstrated ability to balance rapid experimentation with disciplined engineering, designing for scalability, reusability, governance, continuous evaluation, and responsible AI from the outset.
• Candidates must currently reside in an eligible U.S. state for this remote position, including CA, CO, FL, GA, IL, MD, MN, NC, NY, OH, OK, PA, TN, TX, VA, WA, or WV.

Benefits

• Annual base salary: $121,000-$185,000, depending on job-related knowledge, skills, experience, education, and training.
• Eligibility for an annual performance-based bonus, commission, or other variable compensation plan.
• Medical, dental, and other comprehensive employee benefits.
• 401(k) retirement benefits.
• Fully remote, U.S.-based work environment.
• Fast-paced and collaborative culture with significant opportunities for professional growth.
• Inclusive workplace focused on ownership, openness, curiosity, teamwork, and continuous improvement.
• Opportunity to shape enterprise AI strategy, engineering standards, governance, and reusable AI capabilities from an early stage.
• Work on AI initiatives with direct potential to improve operational efficiency, customer experience, and business outcomes.